#!/usr/bin/env python
#=========================================================================
#
#  Copyright NumFOCUS
#
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at
#
#         http://www.apache.org/licenses/LICENSE-2.0.txt
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
#  limitations under the License.
#
#=========================================================================

from __future__ import print_function
from functools import reduce


import SimpleITK as sitk
import sys
import os


def command_iteration(method) :
    if (method.GetOptimizerIteration()==0):
        print("Estimated Scales: ", method.GetOptimizerScales())
    print("{0:3} = {1:7.5f} : {2}".format(method.GetOptimizerIteration(),
                                           method.GetMetricValue(),
                                           method.GetOptimizerPosition()))



if len ( sys.argv ) < 4:
    print( "Usage: {0} <fixedImageFilter> <movingImageFile>  <outputTransformFile>".format(sys.argv[0]))
    sys.exit ( 1 )

pixelType = sitk.sitkFloat32

fixed = sitk.ReadImage(sys.argv[1], sitk.sitkFloat32)


moving = sitk.ReadImage(sys.argv[2], sitk.sitkFloat32)

R = sitk.ImageRegistrationMethod()

R.SetMetricAsCorrelation()

R.SetOptimizerAsRegularStepGradientDescent(learningRate=2.0,
                                           minStep=1e-4,
                                           numberOfIterations=500,
                                           gradientMagnitudeTolerance=1e-8 )
R.SetOptimizerScalesFromIndexShift()

tx = sitk.CenteredTransformInitializer(fixed, moving, sitk.Similarity2DTransform())
R.SetInitialTransform(tx)

R.SetInterpolator(sitk.sitkLinear)

R.AddCommand( sitk.sitkIterationEvent, lambda: command_iteration(R) )

outTx = R.Execute(fixed, moving)

print("-------")
print(outTx)
print("Optimizer stop condition: {0}".format(R.GetOptimizerStopConditionDescription()))
print(" Iteration: {0}".format(R.GetOptimizerIteration()))
print(" Metric value: {0}".format(R.GetMetricValue()))


sitk.WriteTransform(outTx,  sys.argv[3])

if ( not "SITK_NOSHOW" in os.environ ):

    resampler = sitk.ResampleImageFilter()
    resampler.SetReferenceImage(fixed);
    resampler.SetInterpolator(sitk.sitkLinear)
    resampler.SetDefaultPixelValue(1)
    resampler.SetTransform(outTx)

    out = resampler.Execute(moving)

    simg1 = sitk.Cast(sitk.RescaleIntensity(fixed), sitk.sitkUInt8)
    simg2 = sitk.Cast(sitk.RescaleIntensity(out), sitk.sitkUInt8)
    cimg = sitk.Compose(simg1, simg2, simg1//2.+simg2//2.)
    sitk.Show( cimg, "ImageRegistration2 Composition" )
